Case Western Reserve University has built a ground-breaking testing into a new scientific frontier. It utilizes an approach based on three tenets: engineering epidemiology, big data analytics, and prognostics. Dr. Roger French and his team began their efforts in solar research through the opening of the university’s Solar Durability and Lifetime Extension (SDLE) Center. They have expanded their research portfolio to include building envelope efficiency and LED lighting, and are slated to begin work on reliability problems with medical implants and lithium ion batteries.
Lifetime and Degradation Science
In its 2010 Science For Energy Technology workshop, the U.S. Department of Energy Basic Energy Sciences program identified photovoltaic module lifetime and degradation science as an energy research priority. Researchers at the SDLE Center build on years of solar PV industry experience to address this priority, engaging students and industry partners in dynamic research programs that move beyond basic qualification testing of systems to determine actual degradation mechanisms and rates – the scientific underpinning of reliability and qualification standards.
By facilitating this collaborative, applied scientific exploration, the SDLE Center pushes the boundaries of lifetime and degradation science to enable the design of better, longer lasting materials and systems, and accelerated, more accurate testing protocols.
Focusing on solar PV buildings envelope and energy efficiency technologies, the lifetime and degradation science research at the SDLE Center has broader applications to all materials. The advanced exposure techniques, rigorous evaluation processes, and quantitative degradation rate modeling performed at the Center connects materials, components, and systems to address crosscutting research challenges not only for PV, but for all environmentally exposed technologies.
Solar and Energy Data Science Research Led By
- Kyocera ProfessorProfessor, Materials Science and EngineeringDirector, SDLE Research Center
Applies data science and analytics to energy and materials science research problems
- Associate Professor, Materials Science and Engineering
Develops predictive lifetime models for materials degradation related to stress conditions and induced degradation mechanisms evaluated by quantitative spectroscopic characterization of materials